Insights into Therapeutic Response Prediction for Ustekinumab in Ulcerative Colitis Using an Ensemble Bioinformatics Approach

Overview

Journal Int J Mol Sci

Publisher MDPI

Specialties Biochemistry
Chemistry
Molecular Biology

Date 2024 May 25

PMID 38791570

Authors

Kanellos Koustenis

Nikolas Dovrolis

Nikos Viazis

Alexandros Ioannou

Giorgos Bamias

George Karamanolis

Maria Gazouli

Affiliations

Soon will be listed here.

Abstract

Introduction: Optimizing treatment with biological agents is an ideal goal for patients with ulcerative colitis (UC). Recent data suggest that mucosal inflammation patterns and serum cytokine profiles differ between patients who respond and those who do not. Ustekinumab, a monoclonal antibody targeting the p40 subunit of interleukin (IL)-12 and IL-23, has shown promise, but predicting treatment response remains a challenge. We aimed to identify prognostic markers of response to ustekinumab in patients with active UC, utilizing information from their mucosal transcriptome.

Methods: We performed a prospective observational study of 36 UC patients initiating treatment with ustekinumab. Colonic mucosal biopsies were obtained before treatment initiation for a gene expression analysis using a microarray panel of 84 inflammatory genes. A differential gene expression analysis (DGEA), correlation analysis, and network centrality analysis on co-expression networks were performed to identify potential biomarkers. Additionally, machine learning (ML) models were employed to predict treatment response based on gene expression data.

Results: Seven genes, including BCL6, CXCL5, and FASLG, were significantly upregulated, while IL23A and IL23R were downregulated in non-responders compared to responders. The co-expression analysis revealed distinct patterns between responders and non-responders, with key genes like BCL6 and CRP highlighted in responders and CCL11 and CCL22 in non-responders. The ML algorithms demonstrated a high predictive power, emphasizing the significance of the IL23R, IL23A, and BCL6 genes.

Conclusions: Our study identifies potential biomarkers associated with ustekinumab response in UC patients, shedding light on its underlying mechanisms and variability in treatment outcomes. Integrating transcriptomic approaches, including gene expression analyses and ML, offers valuable insights for personalized treatment strategies and highlights avenues for further research to enhance therapeutic outcomes for patients with UC.

References

Henriksen M, Jahnsen J, Lygren I, Stray N, Sauar J, Vatn M . C-reactive protein: a predictive factor and marker of inflammation in inflammatory bowel disease. Results from a prospective population-based study. Gut. 2008; 57(11):1518-23. DOI: 10.1136/gut.2007.146357. View

Arijs I, Li K, Toedter G, Quintens R, Van Lommel L, Van Steen K . Mucosal gene signatures to predict response to infliximab in patients with ulcerative colitis. Gut. 2009; 58(12):1612-9. DOI: 10.1136/gut.2009.178665. View

Knowles S, Graff L, Wilding H, Hewitt C, Keefer L, Mikocka-Walus A . Quality of Life in Inflammatory Bowel Disease: A Systematic Review and Meta-analyses-Part I. Inflamm Bowel Dis. 2018; 24(4):742-751. DOI: 10.1093/ibd/izx100. View

Burisch J, Katsanos K, Christodoulou D, Barros L, Magro F, Pedersen N . Natural Disease Course of Ulcerative Colitis During the First Five Years of Follow-up in a European Population-based Inception Cohort-An Epi-IBD Study. J Crohns Colitis. 2018; 13(2):198-208. DOI: 10.1093/ecco-jcc/jjy154. View

He M, Li C, Tang W, Kang Y, Zuo Y, Wang Y . Machine learning gene expression predicting model for ustekinumab response in patients with Crohn's disease. Immun Inflamm Dis. 2021; 9(4):1529-1540. PMC: 8589399. DOI: 10.1002/iid3.506. View

Gisbert J, Parody-Rua E, Chaparro M . Efficacy, Effectiveness, and Safety of Ustekinumab for the Treatment of Ulcerative Colitis: A Systematic Review. Inflamm Bowel Dis. 2023; 30(2):292-302. PMC: 10834158. DOI: 10.1093/ibd/izac275. View

Vulcano M, Albanesi C, Stoppacciaro A, Bagnati R, DAmico G, Struyf S . Dendritic cells as a major source of macrophage-derived chemokine/CCL22 in vitro and in vivo. Eur J Immunol. 2001; 31(3):812-22. DOI: 10.1002/1521-4141(200103)31:3<812::aid-immu812>3.0.co;2-l. View

Globig A, Sommer N, Wild K, Schardey J, Zoldan K, Thomann A . Ustekinumab Inhibits T Follicular Helper Cell Differentiation in Patients With Crohn's Disease. Cell Mol Gastroenterol Hepatol. 2020; 11(1):1-12. PMC: 7593584. DOI: 10.1016/j.jcmgh.2020.07.005. View

Pavlidis P, Tsakmaki A, Pantazi E, Li K, Cozzetto D, Digby-Bell J . Interleukin-22 regulates neutrophil recruitment in ulcerative colitis and is associated with resistance to ustekinumab therapy. Nat Commun. 2022; 13(1):5820. PMC: 9530232. DOI: 10.1038/s41467-022-33331-8. View

10.

Hindryckx P, Vande Casteele N, Novak G, Khanna R, DHaens G, Sandborn W . The Expanding Therapeutic Armamentarium for Inflammatory Bowel Disease: How to Choose the Right Drug[s] for Our Patients?. J Crohns Colitis. 2017; 12(1):105-119. DOI: 10.1093/ecco-jcc/jjx117. View

11.

Gazouli M, Dovrolis N, Bourdakou M, Gizis M, Kokkotis G, Kolios G . Response to Anti-α4β7 Blockade in Patients With Ulcerative Colitis Is Associated With Distinct Mucosal Gene Expression Profiles at Baseline. Inflamm Bowel Dis. 2021; 28(1):87-95. DOI: 10.1093/ibd/izab117. View

12.

Dovrolis N, Katifelis H, Grammatikaki S, Zakopoulou R, Bamias A, Karamouzis M . Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma. Cancers (Basel). 2023; 15(23). PMC: 10705515. DOI: 10.3390/cancers15235637. View

13.

Gazouli M, Dovrolis N, Franke A, Spyrou G, Sechi L, Kolios G . Differential genetic and functional background in inflammatory bowel disease phenotypes of a Greek population: a systems bioinformatics approach. Gut Pathog. 2019; 11:31. PMC: 6570833. DOI: 10.1186/s13099-019-0312-y. View

14.

Ueyama H, Kiyohara T, Sawada N, Isozaki K, Kitamura S, Kondo S . High Fas ligand expression on lymphocytes in lesions of ulcerative colitis. Gut. 1998; 43(1):48-55. PMC: 1727192. DOI: 10.1136/gut.43.1.48. View

15.

Gisbert J, Chaparro M . Predictors of Primary Response to Biologic Treatment [Anti-TNF, Vedolizumab, and Ustekinumab] in Patients With Inflammatory Bowel Disease: From Basic Science to Clinical Practice. J Crohns Colitis. 2019; 14(5):694-709. DOI: 10.1093/ecco-jcc/jjz195. View

16.

Burczynski M, Peterson R, Twine N, Zuberek K, Brodeur B, Casciotti L . Molecular classification of Crohn's disease and ulcerative colitis patients using transcriptional profiles in peripheral blood mononuclear cells. J Mol Diagn. 2006; 8(1):51-61. PMC: 1867573. DOI: 10.2353/jmoldx.2006.050079. View

17.

Ma B, Meng F, Yan G, Yan H, Chai B, Song F . Diagnostic classification of cancers using extreme gradient boosting algorithm and multi-omics data. Comput Biol Med. 2020; 121:103761. DOI: 10.1016/j.compbiomed.2020.103761. View

18.

Scholer D, Kostev K, Peters M, Zamfir C, Wolk A, Roderburg C . Machine Learning Can Predict the Probability of Biologic Therapy in Patients with Inflammatory Bowel Disease. J Clin Med. 2022; 11(15). PMC: 9369980. DOI: 10.3390/jcm11154586. View

19.

Verstockt B, Verstockt S, Veny M, Dehairs J, Arnauts K, Van Assche G . Expression Levels of 4 Genes in Colon Tissue Might Be Used to Predict Which Patients Will Enter Endoscopic Remission After Vedolizumab Therapy for Inflammatory Bowel Diseases. Clin Gastroenterol Hepatol. 2019; 18(5):1142-1151.e10. PMC: 7196933. DOI: 10.1016/j.cgh.2019.08.030. View

20.

Parigi T, Iacucci M, Ghosh S . Blockade of IL-23: What is in the Pipeline?. J Crohns Colitis. 2022; 16(Supplement_2):ii64-ii72. PMC: 9097679. DOI: 10.1093/ecco-jcc/jjab185. View